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| 1 | Network-Connected UAV Communications: Potentials and Challenges显示文摘This article explores the use of network-connected unmanned aerial vehicle(UAV) communications as a compelling solution to achieve high-rate information transmission and support ultra-reliable UAV remote command and control. We first discuss the use cases of UAVs and the resulting communication requirements, accompanied with a flexible architecture for network-connected UAV communications. Then, the signal transmission and interference characteristics are theoretically analyzed, and subsequently we highlight the design and optimization considerations, including antenna design, nonorthogonal multiple access communications, as well as network selection and association optimization. Finally, case studies are provided to show the feasibility of network-connected UAV communications. | Haichao Wang Jinlong Wang Jin Chen Yuping Gong Guoru Ding | 2018 | China Communications2018，15，12： | 14 |
| 2 | HF Communications: Past, Present, and Future显示文摘High frequency(HF) communication, commonly covering frequency range between 3 and 30 MHz, is an important wireless communication paradigm to offer over-thehorizon or even global communications with ranges up to thousands of kilometers via skywave propagation with ionospheric refraction. It has widespread applications in fields such as emergency communications in disaster areas, remote communications with aircrafts or ships and non-light-of-the-sight military operations. This tutorial article overviews the history of HF communication, demystifies the recent advances, and provides a preview of the next few years, which the authors believe will see fruitful outputs towards wideband, intelligent and integrated HF communications. Specifically, we first present brief preliminaries on the unique features of HF communications to facilitate general readers in the communication community. Then, we provide a historical review to show the technical evolution on the three generations of HF communication systems. Further, we highlight the key challenges and research directions. We hope that this article will stimulate more interests in addressing the technical challenges on the research and development of future HF radio communication systems. | Jinlong Wang Guoru Ding Haichao Wang | 2018 | China Communications2018，15，9： | 12 |
| 3 | Consensus-based decentralized clustering for cooperative spectrum sensing in cognitive radio networks显示文摘A large number of previous works have demonstrated that cooperative spectrum sensing(CSS) among multiple users can greatly improve detection performance.However,when the number of secondary users(SUs;i.e.,spectrum sensors) is large,the sensing overheads(e.g.,time and energy consumption) will likely be intolerable if all SUs participate in CSS.In this paper,we proposed a fully decentralized CSS scheme based on recent advances in consensus theory and unsupervised learning technology.Relying only on iteratively information exchanges among one-hop neighbors,the SUs with potentially best detection performance form a cluster in an ad hoc manner.These SUs take charge of CSS according to an average consensus protocol and other SUs outside the cluster simply overhear the sensing outcomes.For comparison,we also provide a decentralized implementation of the existing centralized optimal soft combination(OSC) scheme.Numerical results show that the proposed scheme has detection performance comparable to that of the OSC scheme and outperforms the equal gain combination scheme and location-awareness scheme.Meanwhile,compared with the OSC scheme,the proposed scheme significantly reduces the sensing overheads and does not require a priori knowledge of the local received signal-to-noise ratio at each SU. | WU QiHui DING GuoRu WANG JinLong LI XiaoQiang HUANG YuZhen | 2012 | Chinese Science Bulletin2012，57，28： | 10 |
| 4 | Cross-Band Spectrum Prediction Based on Deep Transfer Learning显示文摘Spectrum prediction is a promising technology to infer future spectrum state by exploiting inherent patterns of historical spectrum data.In practice,for a given spectrum band of interest,when facing relatively scarce historical data,spectrum prediction based on traditional learning methods does not work well.Thus,this paper proposes a cross-band spectrum prediction model based on transfer learning.Firstly,by analysing service activities and computing the distances between various frequency points based on Dynamic Time Warping,the similarity between spectrum bands has been verified.Next,the features,which mainly affect the performance of transfer learning in the crossband spectrum prediction,are explored by leveraging transfer component analysis.Then,the effectiveness of transfer learning for the cross-band spectrum prediction has been demonstrated.Further,experimental results with real-world spectrum data demonstrate that the performance of the proposed model is better than the state-of-theart models when the historical spectrum data is limited. | Fandi Lin Jin Chen Jiachen Sun Guoru Ding Ling Yu | 2020 | China Communications2020，17，2： | 8 |
| 5 | Proactive optimization of transmission power and 3D trajectory in UAV-assisted relay systems with mobile ground users显示文摘In this paper,an Unmanned Aerial Vehicle(UAV)-assisted relay communication system is studied,where a UAV is served as a flying relay to maintain a communication link between a mobile source node and a remote destination node.Specifically,an average outage probability minimization problem is formulated firstly,with the constraints on the transmission power of the source node,the maximum energy consumption budget,the transmission power,the speed and acceleration of the flying UAV relay.Next,the closed-form of outage probability is derived,under the hybrid line-of-sight and non-line-of-sight probability channel model.To deal with the formulated nonconvex optimization,a long-term proactive optimization mechanism is developed.In particular,firstly,an approximation for line-of-sight probability and a reformulation of the primal problem are given,respectively.Then,the reformulated problem is transformed into two subproblems:one is the transmission power optimization with given UAV’s trajectory and the other is the trajectory optimization with given transmission power allocation.Next,two subproblems are tackled via tailoring primal–dual subgradient method and successive convex approximation,respectively.Furthermore,a proactive optimization algorithm is proposed to jointly optimize the transmission power allocation and the three-dimensional trajectory.Finally,simulation results demonstrate the performance of the proposed algorithm under various parameter configurations. | Jiangchun GU Guoru DING Yitao XU Haichao WANG Qihui WU | 2021 | Chinese Journal of Aeronautics2021，34，3： | 7 |
| 6 | Spatial-temporal spectrum hole discovery:a hybrid spectrum sensing and geolocation database framework显示文摘A hybrid spectrum sensing and geolocation database framework is proposed to tackle the discovery of spatial-temporal spectrum hole in cognitive radio networks.We first analyze the advantages and disadvantages of spectrum sensing-based and geolocation database-based approaches respectively,which motivate us to further propose a hybrid protocol framework by effectively integrating the benefits of both spectrum sensing and geolocation database.Specifically,in the proposed hybrid approach,the goal is to maximize the utilization of spatialtemporal spectrum hole while satisfying the protection constraints for the primary users.Analytical and numerical results demonstrate the superior performance of the proposed hybrid approach over the existing spectrum sensing only and geolocation database only approaches,in terms of interference-free throughput.This article serves as a fundamental framework for advancing the design of hybrid approaches for spatial-temporal spectrum hole discovery. | Jinlong Wang Guoru Ding Qihui Wu Liang Shen Fei Song | 2014 | Chinese Science Bulletin2014，59，16： | 6 |
| 7 | Frequency-Hopping Frequency Reconnaissance and Prediction for Non-cooperative Communication Network显示文摘The continuous change of communica-tion frequency brings difficulties to the reconnaissance and prediction of non-cooperative communication net-works.Since the frequency-hopping(FH)sequence is usually generated by a certain model with certain regularity,the FH frequency is thus predictable.In this paper,we investigate the FH frequency reconnais-sance and prediction of a non-cooperative communi-cation network by effective FH signal detection,time-frequency(TF)analysis,wavelet detection and fre-quency estimation.With the intercepted massive FH signal data,long short-term memory(LSTM)neural network model is constructed for FH frequency pre-diction.Simulation results show that our parameter es-timation methods could estimate frequency accurately in the presence of certain noise.Moreover,the LSTM-based scheme can effectively predict FH frequency and frequency interval. | Gao Li Wei Wang Guoru Ding Qihui Wu Zitong Liu | 2021 | China Communications2021，18，12： | 4 |
| 8 | Spectrum Prediction Based on GAN and Deep Transfer Learning:A Cross-Band Data Augmentation Framework显示文摘This paper investigates the problem of data scarcity in spectrum prediction.A cognitive radio equipment may frequently switch the target frequency as the electromagnetic environment changes.The previously trained model for prediction often cannot maintain a good performance when facing small amount of historical data of the new target frequency.Moreover,the cognitive radio equipment usually implements the dynamic spectrum access in real time which means the time to recollect the data of the new task frequency band and retrain the model is very limited.To address the above issues,we develop a crossband data augmentation framework for spectrum prediction by leveraging the recent advances of generative adversarial network(GAN)and deep transfer learning.Firstly,through the similarity measurement,we pre-train a GAN model using the historical data of the frequency band that is the most similar to the target frequency band.Then,through the data augmentation by feeding the small amount of the target data into the pre-trained GAN,temporal-spectral residual network is further trained using deep transfer learning and the generated data with high similarity from GAN.Finally,experiment results demonstrate the effectiveness of the proposed framework. | Fandi Lin Jin Chen Guoru Ding Yutao Jiao Jiachen Sun Haichao Wang | 2021 | China Communications2021，18，1： | 3 |
| 9 | Multi-Domain Cognition for Cognitive Wireless Networks显示文摘 | DING Guoru WU Qihui WANG Jinlong ef al | 2011 | Frequenz2011，65，1112： | 1 |
| 10 | Spectrum Sensing in Op- portunity-Heterogeneous Cognitive Sensor Networks : How to Coop- erate 显示文摘 | Ding Guoru Wu Qihui Song Fei | 2013 | IEEE Sensor Journal2013，13，11： | 1 |
| 11 | Joint Spectrum Sensing and Transmit Power Adaptation in Interference-aware Cognitive Radio Networks显示文摘 | Ding Guoru Wu Qihui Zou Yulong | 2014 | Transactions on Emerging Telecommunications Technologies2014，25，2： | 1 |
| 12 | Performance analysis of probabilistic soft SSDF attack in cooperative spectrum sensing显示文摘 | Zhang Linyuan Wu Qihui Ding Guoru | 2014 | Eurasip Journal on Advances in Signal Processing2014，81，1： | 1 |
| 13 | Exploration and implementation of a pre-impact fall recognition method based on an inertial body sensor network显示文摘 | Zhao Guoru Mei Zhanyong Liang Ding | | 0，，： | 1 |
| 14 | Kernel-based Learning for statistical signal processing in cognitive radio networks 显示文摘 | Ding Guoru Wu Qihui Yao Yu-Dong et aI | 2013 | IEEE Signal Processing Magazine2013，，： | 1 |
| 15 | Performance Analysis of Probabilistic Soft SSDF Attack in Cooperative Spectrum Sensing显示文摘 | Zhang Linyuan Wu Qihui Ding Guoru | 2014 | EURASIP Journal on Advances in Signal Processing2014，，1： | 1 |
| 16 | Robust Spectrum Sensing With Crowd Sensors显示文摘 | Ding Guoru Wang Jinlong Wu Qihui | 2014 | IEEE Transactions on Communications2014，62，9： | 1 |
| 17 | Topology tracking of dynamic UAV wireless networks显示文摘Wireless network is the communication foundation that supports the intelligentization of Unmanned Aerial Vehicle(UAV) swarm. The topology of UAV communication network is the key to understanding and analyzing the behavior of UAV swarm, thus supporting the further prediction of UAV operations. However, the UAV swarm network topology varies over time due to the high mobility and diversified mission requirements of UAVs. Therefore, it is important but challenging to research dynamic topology inference for tracking the topology changes of the UAV network,especially in non-cooperative manner. In this paper, we study the problem of inferring UAV swarm network topology based on external observations, and propose a dynamic topology inference method. First, we establish a sensing framework for acquiring the communication behavior of the target network over time. Then, we expand the multi-dimensional dynamic Hawkes process to model the communication event sequence in a dynamic wireless network. Finally, combining the sliding time window mechanism, the maximum weighted likelihood estimation is applied to inferring the network topology. Extensive simulation results demonstrate the effectiveness of the proposed method. | Yehui SONG Guoru DING Jiachen SUN Jinghua LI Yitao XU | 2022 | Chinese Journal of Aeronautics2022，35，11： | 0 |
| 18 | Cognitive J^(2)SAC:Joint Jamming,Sensing,and Communication Under Antagonistic Environment显示文摘Integrated sensing and communication(ISAC)is regarded as a recent advanced technology,which is expected to realize the dual functions of sensing and communication simultaneously in one system.Nevertheless,it still faces the challenges of the information security and transmission robustness caused by the openness of wireless channel,especially under antagonistic environment.Hence,this article develops a generalized framework,named cognitive joint jamming,sensing and communication(cognitive J2SAC),to empower the current sensing/communication/jamming system with a“brain”for realizing precise sensing,reliable communication and effective jamming under antagonistic environment.Three kinds of gains can be captured by cognitive J2SAC,including integrated gain,cooperative gain and cognitive gain.Moreover,we highlight the enabling mechanism among jamming,sensing,and communication,as well as illustrating several typical use cases of cognitive J2SAC.Furthermore,several key enabled technologies are analyzed and a typical sensing enhance integrated communication and jamming case study is discussed to verify the effectiveness of the proposed method.Last but not the least,the future directions are listed before concluding this article.Integrated sensing and communication(ISAC)is regarded as a recent advanced technology,which is expected to realize the dual functions of sensing and communication simultaneously in one system.Nevertheless,it still faces the challenges of the information security and transmission robustness caused by the openness of wireless channel,especially under antagonistic environment.Hence,this article develops a generalized framework,named cognitive joint jamming,sensing and communication(cognitive J2SAC),to empower the current sensing/communication/jamming system with a“brain”for realizing precise sensing,reliable communication and effective jamming under antagonistic environment.Three kinds of gains can be captured by cognitive J2SAC,including integrated gain,cooperative gain and cognitive gain.Moreover,we highlight the enabling mechanism among jamming,sensing,and communication,as well as illustrating several typical use cases of cognitive J2SAC.Furthermore,several key enabled technologies are analyzed and a typical sensing enhance integrated communication and jamming case study is discussed to verify the effectiveness of the proposed method.Last but not the least,the future directions are listed before concluding this article. | Jiangchun Gu Guoru Ding Yizhen Yin Haichao Wang Yitao Xu Yehui Song | 2023 | China Communications2023，20，9： | 0 |
| 19 | Edge Semantic Cognitive Intelligence for 6G Networks:Novel Theoretical Models,Enabling Framework,and Typical Applications显示文摘Edge intelligence is anticipated to underlay the pathway to connected intelligence for 6G networks,but the organic confluence of edge computing and artificial intelligence still needs to be carefully treated.To this end,this article discusses the concepts of edge intelligence from the semantic cognitive perspective.Two instructive theoretical models for edge semantic cognitive intelligence(ESCI)are first established.Afterwards,the ESCI framework orchestrating deep learning with semantic communication is discussed.Two representative applications are present to shed light on the prospect of ESCI in 6G networks.Some open problems are finally listed to elicit the future research directions of ESCI. | Peihao Dong Qihui Wu Xiaofei Zhang Guoru Ding | 2022 | China Communications2022，19，8： | 0 |
| 20 | An informational perspective of semantic cognition process显示文摘Information theory(IT)is the derivation and foundation of information science,and has become one of the most mature,complete and systematic components in information and communication fields within these years.This article extends classic IT from the traditional form aspect to the semantic aspect and gives an informational perspective of semantic cognition process(SCP),which is motivated by the stringent requirements of information predigestion and machine cognition in cognitive wireless networks.To begin with,we establish three key viewpoints on semantic,which are semantic objectivity,semantic conditional uniformity and semantic dependency,as the basis and premise of this article.Next,we establish a comprehensive theoretical framework of SCP in terms of the natural connotation,the three-layer framework and the mathematical model of SCP.Then we give a couple of primary theorems of SCP as well as their practical instructions.Furthermore,the research challenges ahead are presented in this article. | Shuo Feng Qihui Wu Jinlong Wang Xueqiang Zheng Yuhua Xu Guoru Ding | 2014 | Chinese Science Bulletin2014，59，14： | 0 |
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